Abstract:
Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.
Abstract:
Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.
Abstract:
Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.
Abstract:
Gemäß einem Verfahren für den Zugriff auf einen gemeinsam genutzten Datensatz bei gleichzeitigem Lese- und Schreibzugriff mehrerer Anforderer liest ein Anforderer einen gemeinsam genutzten Datensatz, der Nutzdaten und eine erste Prüfsumme enthält. Der Anforderer berechnet eine zweite Prüfsumme der Nutzdaten des Datensatzes. Sind die erste und zweite Prüfsumme nicht gleich, liest der Anforderer erneut den gemeinsam genutzten Datensatz, der eine dritte Prüfsumme enthält, und berechnet eine vierte Prüfsumme der Nutzdaten des gemeinsam genutzten Datensatzes. Sind die dritte und vierte Prüfsumme gleich, verarbeitet der Anforderer den gemeinsam genutzten Datensatz als gültig, und wenn die zweite und vierte Prüfsumme gleich sind, behandelt der Anforderer den gemeinsam genutzten Datensatz als beschädigt.
Abstract:
A method, system, and computer usable program product for detecting a no progress state of an application are provided in the illustrative embodiments. A resource usage and an output of a set of applications are monitored. The resource usage and the output are measured to determine a resource usage value and an output value at a given time. A determination is made whether the resource usage value is included in a sub-range of a resource usage scale and the output value is included in a sub-range of an output scale where the sub-range of the resource usage scale corresponds to the sub-range of the output scale. The no progress state of the application is detected if the determination is negative.
Abstract:
Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.
Abstract:
According to a method of access to a shared data record subject to contemporaneous read and write access by multiple requesters, a requester reads a shared data record including a payload and a first checksum. The requester calculates a second checksum of the payload of the data record. If the first and second checksums are not equal, the requester again reads the shared data record, including a third checksum, and calculates a fourth checksum of the payload of the shared data record. If the third and fourth checksums are equal, the requester processes the shared data record as valid, and if the second and fourth checksums are equal, the requester handles the shared data record as corrupt.
Abstract:
Ein Verfahren, System und von einem Computer verwendbares Programmprodukt zum Erkennen eines Kein-Fortschritt-Zustands einer Anwendung werden in den veranschaulichenden Ausführungsformen bereitgestellt. Eine Ressourcen-Inanspruchnahme und eine Ausgangsleistung einer Anwendungsgruppe werden überwacht. Die Ressourcen-Inanspruchnahme und die Ausgangsleistung werden gemessen, um einen Ressourcen-Inanspruchnahmewert und einen Ausgangsleistungswert zu einem vorgegebenen Zeitpunkt zu bestimmen. Eine Bestimmung erfolgt, ob der Ressourcen-Inanspruchnahmewert in einem Unterbereich einer Skala für die Ressourcen-Inanspruchnahme enthalten ist und der Ausgangsleistungswert in einem Unterbereich einer Ausgangsleistungsskala enthalten ist, wobei der Unterbereich der Skala für die Ressourcen-Inanspruchnahme dem Unterbereich der Ausgangsleistungsskala entspricht. Der Kein-Fortschritt-Zustand der Anwendung wird erkannt, wenn die Bestimmung negativ ist.
Abstract:
Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.